Thin-Layer Infrared Drying of Mint Leaves

Comparative evaluation of drying methods for struvite produced from electrocoagulated source-separated urine: Implications for quality, energy and cost-effectiveness

Struvite precipitation from source-separated urine is crucial for waste utilization and sustainability. However, after precipitation, the high moisture content of struvite necessitates an additional drying process that can be costly and inefficient. In the present study, the performance of different drying methods-open sun drying, air drying, conventional drying (20-100 °C), and microwave drying (180-720 W) on the quality of struvite obtained from source-separated urine through electrocoagulation using Mg-Mg electrodes were evaluated. It was found that higher temperatures and power in the convective oven and microwave resulted in higher diffusivity (10-9-10-7 m2s-1), leading to reduced drying times. Different models were employed to comprehend the drying mechanism, and the one with the highest correlation coefficient (R2 = 0.99) and the lowest statistical values was selected. The key findings indicated that higher power and temperature levels were more cost-effective. However, characterization of the dried struvite using X-ray diffraction and Fourier-transformed infrared spectroscopy, disintegration of struvite crystals at temperatures above 60 °C in the conventional oven and 180 W in the microwave oven was observed. Based on the results, we conclude that sun drying is a cost-effective and environmentally friendly alternative for drying struvite without compromising its quality.

Utilizing of the Common Dehydrating Techniques to obtain maximum benefit from the Protein and mineral Composition of rosemary leaves for Spice and Herbal Tea Production

In the study, we examined in detail the effect of dehydrating using natural drying in the shade, convection drying, and microwave drying, which are the most widely used techniques, especially for tea and spices, both in practice and in theory, on the protein, and mineral composition of rosemary leaves. Also, we determined the color parameters, which are the reason for the selection because it creates the allure for spices. In microwave drying at 600 W, we obtained results close to fresh rosemary in all color parameters, especially brightness and greenness. Although natural drying, which does not have any energy and investment costs, is the second-best method in terms of color, 50 °C, which is the most common drying technique in the market, caused significant color losses affecting the commercial value of the product. We reached the closest protein and P, Ca, Mg, Fe, Zn, Mn, and contents to fresh products in dried ones at 600 W. In contrast, in K only, the highest measurement was at 200 W. Strikingly, we observed dramatic losses reducing the benefit obtained from the product regarding protein and almost all nutrients in both convective and natural drying techniques, the most common methods in practice.

Mathematical and intelligent modeling of stevia (Stevia Rebaudiana) leaves drying in an infrared-assisted continuous hybrid solar dryer

Drying characteristics of stevia leaves were investigated in an infrared (IR)-assisted continuous-flow hybrid solar dryer. Drying experiments were conducted at the inlet air temperatures of 30, 40, and 50°C, air inlet velocities of 7, 8, and 9 m/s, and IR lamp input powers of 0, 150, and 300 W. The results indicated that inlet air temperature and IR lamp input power had significant effect on drying time (p < .05). A comparative study was performed among mathematical, Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy System (ANFIS) models for predicting the experimental moisture ratio (MR) of stevia leaves during the drying process. The ANN model was the most accurate MR predictor with coefficient of determination (R2), root mean squared error (RMSE), and chi-squared error (χ2) values of 0.9995, 0.0005, and 0.0056, respectively, on test dataset. These values of the ANFIS model on test dataset were 0.9936, 0.0243, and 0.0202, respectively. Among the mathematical models, the Midilli model was the best-fitted model to experimental MR values in most of the drying conditions. It was concluded that artificial intelligence modeling is an effective approach for accurate prediction of the drying kinetics of stevia leaves in the continuous-flow IR-assisted hybrid solar dryer.

Investigating the Influence of Infrared Drying Method on Linden (Tilia platyphyllos Scop.) Leaves: Kinetics, Color, Projected Area, Modeling, Total Phenolic, and Flavonoid Content

The Linden (Tilia platyphyllos Scop.) is a highly popular herbal plant due to its central nervous system properties. In this study, thin layer drying kinetics of linden leave samples were experimentally investigated in an infrared (IR) dryer. In order to select the appropriate model for predicting the drying kinetics of linden leaves, eleven thin layer semi theoretical, theoretical, and empirical models, widely used in describing the drying behavior of agricultural products, were fitted to the experimental data. Moreover, the color, projected area (PA), total phenolic content (TPC), and total flavonoid content (TFC) were investigated. The results showed that the drying time decreased from 50 min to 20 min. with increased IR temperature from 50-70 °C. Therewithal, the Midilli model gave the most suitable data for 50 °C, 60 °C. Moreover, Verma et al. and Diffusion approximation models showed good results for 70 °C. The lightness and greenness of the dried linden leaves were significantly changed compared with fresh samples. The PA of dried sample decreased similar to the drying time. In addition, the drying temperature effect on the effective diffusion diffusivity (D_eff) and activation energy (E_a) were also computed. The D_eff ranges from 4.13 × 10^-12 to 5.89 × 10^-12 and E_a coefficient was 16.339 kJ/mol. Considering these results, the Midilli et al. model is above the 50 °C, 60 °C, and the Verma et al. and Diffusion to 70 °C, for explaining the drying behavior of linden leaves under IR drying. Moreover, it can be said that the Page model can be used, if it is desired, to express the drying behaviors, partially with the help of a simple equation material by drying. TPC and TFC values were statistically < 0.001 higher in dried samples compared to fresh samples; however, no change has been recorded of TPC and TFC values at different temperatures (50 °C, 60 °C, 70 °C).

Infrared drying of dill leaves: Drying characteristics, temperature distributions, performance analyses and colour changes

Thin-layer drying behaviour of dill leaves samples under three different infrared radiation power intensities was investigated. Diffusion Approach was found to be the best model that describes the drying behaviour of dill leaves. Effective diffusivity values were 6.97 × 10^-9, 6.84 × 10^-9 and 8.96 × 10^-9 m²/s for power intensities of 1790, 1970 and 2070 W/m², respectively. According to the first and second law efficiencies, the infrared drying system was more efficient at higher power intensities (p < 0.05). However, the total colour change was maximum at the highest power intensity. For the investigated infrared drying conditions, 1970 W/m² was recommended as the best-infrared power intensity applied for drying of dill leaves by taking into account both performance analyses and quality changes.

The Effect of Infrared Drying on Color, Projected Area, Drying Time, and Total Phenolic Content of Rose (Rose electron) Petals

The effects of different drying temperatures (50, 60, 70 °C) on the quality of rose (Rose electron) petals were evaluated in this study. Drying time decreased from 1680 s to 600 s with increased infrared temperature. The temperature and time were increased from 50 °C to 70 °C and 30 min to 60 min, respectively, and a decrease in the fruit color quality was observed. The projected area (PA) of rose petals was affected significantly from temperature. After the drying process, the largest PA was observed as 33.35 cm² (50 °C, 30 min), while the smallest achieved at 70 °C, 60 min (27.96 cm²). Depending on the temperature values (50, 60, 70 °C), the average projection area of dry samples of the rose petals decreased 2.17 times compared to the projection area of fresh samples. The dried samples demonstrated an increase in the total phenolic (TP) content compared to the fresh samples. The maximum TP (44.49 mg GAE/g) was achieved at 45 min and 70 °C rose petals sample. The results concluded that infrared drying for 45 min at 70 °C could be recommended for drying rose (rosa electron) petals.